SIM card identifiers

Identifies documents containing references to sim card identifiers in international contexts. This information type is classified as personally identifiable information under applicable data protection regulations.

Type: regex
Engine: boost_regex
Confidence: medium
Confidence justification: identifier/document-structure anchored regex with constrained context replaces phrase-only detection. Added context gating and exclusion rules improve precision and reduce incidental matches.
Detection quality: Mixed
Jurisdictions: global
Regulations: GDPR
Data categories: pii
Scope: wide
Platform compatibility: Purview: Compatible, GCP DLP: Compatible, Macie: Compatible, Zscaler: Compatible, Palo Alto: Compatible, Netskope: Compatible

Pattern

\b89\d{17,18}\b

Corroborative evidence keywords

sim card identifiers, sim, card, identifiers, contact, location, data, file number, reference number, case number, record number, account number, serial number, identification number, registration number, customer number, member number, reference code, ID number, data record (+11 more)

Proximity: 300 characters

Should match

89014103211118510720 — 20-digit ICCID
8910390000000000001 — 19-digit ICCID
89140000000000000007 — ICCID starting 8914

Should not match

1234567890 — Not an ICCID
8901 — Too short
template example placeholder — Template/sample text

Known false positives

Common words and phrases related to sim card identifiers appearing in policy documents, training materials, HR templates, or compliance guidelines without actual personal data. Mitigation: Require corroborative evidence keywords within the proximity window to confirm sensitive data context rather than general discussion.
In English (as the primary international business language), similar terminology used in formal or administrative contexts (education, professional documentation) that does not constitute sensitive data collection. Mitigation: Layer with additional contextual signals such as structured identifiers, form fields, or database column headers to distinguish sensitive records from general references.
High-frequency pattern matches in large document corpora due to broad regex anchors. Expected match rate is significantly higher than specific identifier patterns. Mitigation: Tune confidence thresholds for bulk scanning. Consider using this pattern primarily as a pre-filter with secondary validation.

References

https://eur-lex.europa.eu/eli/reg/2016/679/oj
https://www.oaic.gov.au/privacy/your-privacy-rights/your-personal-information/what-is-personal-information